# SPDX-License-Identifier: Apache-2.0
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project

from dataclasses import dataclass
from pathlib import Path
from typing import Literal

import torch
from PIL import Image

from .base import get_vllm_public_assets

VLM_IMAGES_DIR = "vision_model_images"

ImageAssetName = Literal[
    "stop_sign",
    "cherry_blossom",
    "hato",
    "2560px-Gfp-wisconsin-madison-the-nature-boardwalk",
    "Grayscale_8bits_palette_sample_image",
    "1280px-Venn_diagram_rgb",
    "RGBA_comp",
    "237-400x300",
    "231-200x300",
    "27-500x500",
    "17-150x600",
    "handelsblatt-preview",
    "paper-11",
]


@dataclass(frozen=True)
class ImageAsset:
    name: ImageAssetName

    def get_path(self, ext: str) -> Path:
        """
        Return s3 path for given image.
        """
        return get_vllm_public_assets(
            filename=f"{self.name}.{ext}", s3_prefix=VLM_IMAGES_DIR
        )

    @property
    def pil_image(self) -> Image.Image:
        return self.pil_image_ext(ext="jpg")

    def pil_image_ext(self, ext: str) -> Image.Image:
        image_path = self.get_path(ext=ext)
        return Image.open(image_path)

    @property
    def image_embeds(self) -> torch.Tensor:
        """
        Image embeddings, only used for testing purposes with llava 1.5.
        """
        image_path = self.get_path("pt")
        return torch.load(image_path, map_location="cpu", weights_only=True)

    def read_bytes(self, ext: str) -> bytes:
        p = Path(self.get_path(ext))
        return p.read_bytes()